Multi-objective variable neighborhood search: an application to combinatorial optimization problems

Duarte, Abraham; Pantrigo, Juan José; Pardo, Eduardo G.; Mladenović, Nenad

doi:10.1007/s10898-014-0213-z

Cited by 82 publications

(62 citation statements)

References 29 publications

(32 reference statements)

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“…Duarte et al. () presented an adaptation of three variants of the VNS metaheuristic for solving multiobjective optimization problems, namely multiobjective reduced VNS (MO‐RVNS), multiobjective variable neighborhood descent (MO‐VND), and MO‐GVNS. These variants are used to solve two multiobjective combinatorial optimization problems, that is, the multiobjective knapsack problem and the multiobjective antibandwidth–cutwidth problem.…”

Section: Introductionmentioning

confidence: 99%

“…Inspired by these successful MO‐VNS applications, in this work we propose an adaptation of the MO‐GVNS algorithm presented in Duarte et al. () for solving the addressed MOHFS problem. As in Duarte et al.…”

Section: Introductionmentioning

confidence: 99%

“…As in Duarte et al. (), our adapted algorithm also uses MO‐VND as the local search method. However, while MO‐VND proposed by those authors improves each objective function separately, in our proposal the MO‐VND method is used for improving all objective functions simultaneously.…”

Section: Introductionmentioning

confidence: 99%

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An MO‐GVNS algorithm for solving a multiobjective hybrid flow shop scheduling problem

Siqueira

Souza

2019

Int Trans Operational Res

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This paper addresses the multiobjective hybrid flow shop (MOHFS) scheduling problem. In the MOHFS problem considered here, we have a set of jobs that must be performed in a set of stages. At each stage, we have a set of unrelated parallel machines. Some jobs may skip stages. The evaluation criteria are the minimizations of makespan, the weighted sum of the tardiness, and the weighted sum of the earliness. For solving it, an algorithm based on the multiobjective general variable neighborhood search (MO‐GVNS) metaheuristic, named adapted MO‐GVNS, is proposed. This work also presents and compares the results obtained by the adapted MO‐GVNS with those of four other algorithms: multiobjective reduced variable neighborhood search, nondominated sorting genetic algorithm II (NSGA‐II), and NSGA‐III, and another MO‐GVNS from the literature. The results were evaluated based on the Hypervolume, Epsilon, and Spacing metrics, and statistically validated by the Levene test and confidence interval charts. The results showed the efficiency of the proposed algorithm for solving the MOHFS problem.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An MO‐GVNS algorithm for solving a multiobjective hybrid flow shop scheduling problem

Siqueira

Souza

2019

Int Trans Operational Res

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“…On the other hand, in Duarte et al (2015), the VNS metaheuristic adaptation is explored along with its extensions to solve multi-objective combinatorial problems. To achieve the objective, the solution concept is redefined and adapted to the multi-objective context, where a set of solutions called approximated set of efficient solutions is taken.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective MDVRP solution considering route balance and cost using the ILS metaheuristic

Galindres-Guancha¹,

Toro-Ocampo²,

Rendón³

2018

10.5267/j.ijiec

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The multi-objective problem of multi-depot vehicle routing (MOMDVRP) is proposed by considering the minimization of the traveled arc costs and the balance of routes. Seven mathematical models were reviewed to determine the route balance equation and the bestperforming model is selected for this purpose. The solution methodology consists of three stages; in the first one, beginning solutions are built up by means of a constructive heuristic. In the second stage, fronts are constructed from each starting solution using the iterated local search multi-objective metaheuristics (ILSMO). In the third stage, we obtain a single front by using concepts of dominance, taking as a base the fronts of the previous stage. Thus, the first two fronts are taken and a single front is formed that corresponds to the current solution of the problem; next the third front is added to the current Pareto front of the problem, the procedure is repeated until exhaustion of the list of the fronts initially obtained. The resulting front is the solution to the problem. To validate the methodology we use instances from the specialized literature, which have been used for the multi-depot routing problem (MDVRP). The results obtained provide very good quality. Finally, decision criteria are used to select the most appropriate solution for the front, both from the point of view of the balance and the route cost.

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“…The vehicle scheduling problem and the optimal allocation of resources are combinatorial optimization problems [4][5], the multi machine scheduling problem is also included. Sun F [6] studied the multiple machine scheduling problem based on fuzzy operation time.…”

Section: Introductionmentioning

confidence: 99%

Research on Weighing Strategy of Vehicle Entering Plant Based on Fuzzy Operation Time

Chen¹,

Wang²

2017

dtetr

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Abstract. In order to solve the problem of congestion and disorder in the process of weighing and handling of cement vehicles entering the plant, a new scheduling strategy based on fuzzy operation time is proposed. Firstly, the modeling and analysis of the problem, and then proposes a genetic algorithm to solve the problem. The algorithm was improved and the different algorithm and the improved algorithm optimization results was compared. The results show that the proposed scheme can effectively solve congestion problems and increase weighing efficiency of vehicle entering plant.

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Multi-objective variable neighborhood search: an application to combinatorial optimization problems

Cited by 82 publications

References 29 publications

An MO‐GVNS algorithm for solving a multiobjective hybrid flow shop scheduling problem

An MO‐GVNS algorithm for solving a multiobjective hybrid flow shop scheduling problem

Multi-objective MDVRP solution considering route balance and cost using the ILS metaheuristic

Research on Weighing Strategy of Vehicle Entering Plant Based on Fuzzy Operation Time

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